A Question of Demand and Supply? Defining the Demand and Providing a Supply of Respirologists
Bibliographic record
Abstract
In this issue of the Canadian Respiratory Journal, we are invited to think about respirology manpower in Canada. I believe it is the first time that the Journal has published on the topic, perhaps suprisingly, for the issues that are raised are of great importance to all physicians who care for patients with chest problems. Dr Don Cockcroft and Dr David Wensley (pages 451‐455) conducted a survey of program directors and obtained data regarding Royal College Fellows, which allowed them to estimate the number of chest specialists currently in practice and to predict what will happen to these numbers in the foreseeable future. Based on the numbers and the waiting times for outpatient appointments, their main conclusions are that there is a shortfall in adult respirologists that may be as high as 50%; that the shortfall is at least as large for pediatric specialists; and that current output from training programs is unlikely to meet the shortfalls. Currently, they estimate a total of 361 adult specialists, or one for every 86,000 population, but with regional differences that account for a variation from one to 69,000 in Alberta to one to 253,000 in New Brunswick.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.008 | 0.014 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".